public class RemainderOp extends BaseTransformOp
extraArgs, extraArgz, n, numProcessed, passThrough, x, xVertexId, y, yVertexId, z, zVertexIddimensions, inPlace, sameDiff, scalarValue| Constructor and Description |
|---|
RemainderOp() |
RemainderOp(INDArray x) |
RemainderOp(INDArray x,
INDArray z) |
RemainderOp(INDArray x,
INDArray y,
INDArray z) |
RemainderOp(INDArray x,
INDArray y,
INDArray z,
long n) |
RemainderOp(INDArray x,
INDArray z,
long n) |
RemainderOp(SameDiff sameDiff) |
RemainderOp(SameDiff sameDiff,
SDVariable i_v,
boolean inPlace) |
RemainderOp(SameDiff sameDiff,
SDVariable i_v,
int[] shape,
boolean inPlace,
Object[] extraArgs) |
RemainderOp(SameDiff sameDiff,
SDVariable i_v,
Object[] extraArgs) |
RemainderOp(SameDiff sameDiff,
SDVariable i_v1,
SDVariable i_v2) |
RemainderOp(SameDiff sameDiff,
SDVariable i_v1,
SDVariable i_v2,
boolean inPlace) |
RemainderOp(SameDiff sameDiff,
SDVariable i_v1,
SDVariable i_v2,
Object[] extraArgs) |
| Modifier and Type | Method and Description |
|---|---|
List<SDVariable> |
doDiff(List<SDVariable> f1)
The actual implementation for automatic differentiation.
|
void |
init(INDArray x,
INDArray y,
INDArray z,
long n)
Initialize the operation based on the parameters
|
String |
onnxName()
The opName of this function in onnx
|
String |
opName()
The name of the op
|
int |
opNum()
The number of the op (mainly for old legacy XYZ ops
like
Op) |
String |
tensorflowName()
The opName of this function tensorflow
|
calculateOutputShape, opType, zequals, exec, exec, extraArgs, extraArgsBuff, extraArgsDataBuff, getOpType, hashCode, initFromOnnx, initFromTensorFlow, isExecSpecial, isPassThrough, n, numProcessed, outputVariables, setN, setX, setY, setZ, toCustomOp, toString, x, yarg, args, asProperties, attributeAdaptersForFunction, configFieldName, diff, dup, f, getValue, hasPlaceHolderInputs, isConfigProperties, larg, mappingsForFunction, onnxNames, outputVariables, propertiesForFunction, rarg, resolvePropertiesFromSameDiffBeforeExecution, setInstanceId, setValueFor, tensorflowNamesclone, finalize, getClass, notify, notifyAll, wait, wait, waitexec, exec, extraArgs, extraArgsBuff, extraArgsDataBuff, isExecSpecial, isPassThrough, n, numProcessed, setExtraArgs, setN, setX, setY, setZ, toCustomOp, x, ypublic RemainderOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
public RemainderOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
public RemainderOp(SameDiff sameDiff)
public RemainderOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
public RemainderOp(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
public RemainderOp(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
public RemainderOp(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
public RemainderOp()
public RemainderOp(INDArray x)
public int opNum()
DifferentialFunctionOp)opNum in interface OpopNum in class DifferentialFunctionpublic String opName()
DifferentialFunctionopName in interface OpopName in class DifferentialFunctionpublic String onnxName()
DifferentialFunctiononnxName in class DifferentialFunctionpublic String tensorflowName()
DifferentialFunctiontensorflowName in class DifferentialFunctionpublic void init(INDArray x, INDArray y, INDArray z, long n)
Oppublic List<SDVariable> doDiff(List<SDVariable> f1)
DifferentialFunctiondoDiff in class DifferentialFunctionCopyright © 2018. All rights reserved.